According to the pronouncements of the European Commission,
«Trustworthy AI has three components, which should be met throughout the system’s entire life cycle:

1. It should be lawful, complying with all applicable laws and regulations
2. It should be ethical, ensuring adherence to ethical principles and values and
3. It should be robust, both from a technical and social perspective since, even with good intentions, AI systems can cause unintentional harm. Each component in itself is necessary but not sufficient for the achievement of Trustworthy AI».

Robust, safe, secure & reliable autonomous wheelchair

In the context of social robotic navigation, trustable environmental sensing (e.g., people and obstacle detection, traversability estimation, etc.) is essential to guarantee robustness against uncertainties, malfunctions, and disturbances. A smart-sensing subsystem will be designed with the aim of providing trusted event detection.

Greener AI Solution

Planet-caring is a dimension on which we cannot neglect, today. We will develop a system to orchestrate the fleet of AI-Based Swarm and a dataset optimisation for REXASI-PRO algorithm which is based on topology (in order to compress the dataset without compromising data). Both systems will reduce costs and power consumption.


The functioning of AI system requires appropriate respect for potentially vulnerable persons and groups, such as persons with disabilities and others at risk of exclusion. We will create a multi-phase framework for assessing ethical issues of a Multi-Robot Systems and Data Collection Platform supporting people with mobile disabilities gap. We will apply the ALTAI (Assessment List for Trustworthy AI) and the Roboethics Roadmap to a Multi-Robot Systems and Data Collection Platform supporting people with mobile disabilities gap to define Ethical Legal and Societal requirements in a specific Case Study.


We will work on the definition of a roadmap of the certification and commercialization of autonomous wheelchairs by developing an exploitation strategy to support the adoption solution in the market. It will include an analysis of the main non-economic aspects relevant for a successful implementation.